Uncertainty in the extreme flood magnitude estimates of large-scale flood hazard models
- The growing worldwide impact of flood events has motivated the development and application of global flood hazard models (GFHMs). These models have become useful tools for flood risk assessment and management, especially in regions where little local hazard information is available. One of the key uncertainties associated with GFHMs is the estimation of extreme flood magnitudes to generate flood hazard maps. In this study, the 1-in-100 year flood (Q100) magnitude was estimated using flow outputs from four global hydrological models (GHMs) and two global flood frequency analysis datasets for 1350 gauges across the conterminous US. The annual maximum flows of the observed and modelled timeseries of streamflow were bootstrapped to evaluate the sensitivity of the underlying data to extrapolation. Results show that there are clear spatial patterns of bias associated with each method. GHMs show a general tendency to overpredict Western US gauges and underpredict Eastern US gauges. The GloFAS and HYPE models underpredict Q100 by more thanThe growing worldwide impact of flood events has motivated the development and application of global flood hazard models (GFHMs). These models have become useful tools for flood risk assessment and management, especially in regions where little local hazard information is available. One of the key uncertainties associated with GFHMs is the estimation of extreme flood magnitudes to generate flood hazard maps. In this study, the 1-in-100 year flood (Q100) magnitude was estimated using flow outputs from four global hydrological models (GHMs) and two global flood frequency analysis datasets for 1350 gauges across the conterminous US. The annual maximum flows of the observed and modelled timeseries of streamflow were bootstrapped to evaluate the sensitivity of the underlying data to extrapolation. Results show that there are clear spatial patterns of bias associated with each method. GHMs show a general tendency to overpredict Western US gauges and underpredict Eastern US gauges. The GloFAS and HYPE models underpredict Q100 by more than 25% in 68% and 52% of gauges, respectively. The PCR-GLOBWB and CaMa-Flood models overestimate Q100 by more than 25% at 60% and 65% of gauges in West and Central US, respectively. The global frequency analysis datasets have spatial variabilities that differ from the GHMs. We found that river basin area and topographic elevation explain some of the spatial variability in predictive performance found in this study. However, there is no single model or method that performs best everywhere, and therefore we recommend a weighted ensemble of predictions of extreme flood magnitudes should be used for large-scale flood hazard assessment.…
Author details: | Laura DevittORCiD, Jeffrey NealORCiD, Thorsten WagenerORCiDGND, Gemma CoxonORCiD |
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DOI: | https://doi.org/10.1088/1748-9326/abfac4 |
ISSN: | 1748-9326 |
Title of parent work (English): | Environmental research letters : ERL / Institute of Physics |
Publisher: | IOP Publ. Ltd. |
Place of publishing: | Bristol |
Publication type: | Article |
Language: | English |
Date of first publication: | 2021/05/20 |
Publication year: | 2021 |
Release date: | 2023/06/20 |
Tag: | flood risk; global hydrological model; large-scale flood hazard models |
Volume: | 16 |
Issue: | 6 |
Article number: | 064013 |
Number of pages: | 15 |
Funding institution: | Water Informatics Science and Engineering Centre for Doctoral Training (WISE CDT) under a grant from the Engineering and Physical Sciences Research Council (EPSRC)UK Research & Innovation (UKRI)Engineering & Physical Sciences Research Council (EPSRC) [EP/L016214/1]; Royal Society Wolfson Research Merit AwardRoyal Society of London [WM170042]; Alexander von Humboldt FoundationAlexander von Humboldt Foundation |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
6 Technik, Medizin, angewandte Wissenschaften / 69 Hausbau, Bauhandwerk / 690 Hausbau, Bauhandwerk | |
Peer review: | Referiert |
Publishing method: | Open Access / Gold Open-Access |
License (German): | CC-BY - Namensnennung 4.0 International |